Zehaan Walji

Abstract Trust is a determinant of effective human–AI collaboration, shaping whether users appropriately accept or reject system recommendations. In safety-critical domains, miscalibrated trust can lead to unsafe overrides or uncritical acceptance of erroneous outputs. However, existing trust measurement approaches are often static, rely on subjective self-reports, and struggle to capture dynamic fluctuations during interactions.